Development of a standard sign-out procedure for clinicians in a pediatric intensive care unit

Background: Poor communication among health care providers is cited as the most common cause of sentinel events involving patients. Sign-out of patient data at the change of clinician shifts is a component of communication that is especially vulnerable to errors. Sign-outs are particularly extensive and complex in intensive care units (ICUs). There is a paucity of validated tools to assess ICU sign-outs. ^ Objective: To design a valid and reliable survey tool to assess the perceptions of Pediatric ICU (PICU) clinicians about sign-out. ^ Design: Cross-sectional, web-based survey ^ Setting: Academic hospital, 31-bed PICU ^ Subjects: Attending faculty, fellows, nurse practitioners and physician assistants. ^ Interventions: A survey was designed with input from a focus group and administered to PICU clinicians. Test-retest reliability, internal consistency and validity of the survey tool were assessed. ^ Measurements and Main Results: Forty-eight PICU clinicians agreed to participate. We had 42(88%) and 40(83%) responses in the test and retest phases. The mean scores for the ten survey items ranged from 2.79 to 3.67 on a five point Likert scale with no significant test-retest difference and a Pearson correlation between pre and post answers of 0.65. The survey item scores showed internal consistency with a Cronbach's Alpha of 0.85. Exploratory factor analysis revealed three constructs: efficacy of sign-out process, recipient satisfaction and content applicability. Seventy eight % clinicians affirmed the need for improvement of the sign-out process and 83% confirmed the need for face- to-face verbal sign-out. A system-based sign-out format was favored by fellows and advanced level practitioners while attendings preferred a problem-based format (p=0.003). ^ Conclusions: We developed a valid and reliable survey to assess clinician perceptions about the ICU sign-out process. These results can be used to design a verbal template to improve and standardize the sign-out process.^

TIME SERIES ANALYSIS AS INPUT FOR PREDICTIVE MODELING: PREDICTING CARDIAC ARREST IN A PEDIATRIC INTENSIVE CARE UNIT

The first manuscript, entitled "Time-Series Analysis as Input for Clinical Predictive Modeling: Modeling Cardiac Arrest in a Pediatric ICU" lays out the theoretical background for the project. There are several core concepts presented in this paper. First, traditional multivariate models (where each variable is represented by only one value) provide single point-in-time snapshots of patient status: they are incapable of characterizing deterioration. Since deterioration is consistently identified as a precursor to cardiac arrests, we maintain that the traditional multivariate paradigm is insufficient for predicting arrests. We identify time series analysis as a method capable of characterizing deterioration in an objective, mathematical fashion, and describe how to build a general foundation for predictive modeling using time series analysis results as latent variables. Building a solid foundation for any given modeling task involves addressing a number of issues during the design phase. These include selecting the proper candidate features on which to base the model, and selecting the most appropriate tool to measure them. We also identified several unique design issues that are introduced when time series data elements are added to the set of candidate features. One such issue is in defining the duration and resolution of time series elements required to sufficiently characterize the time series phenomena being considered as candidate features for the predictive model. Once the duration and resolution are established, there must also be explicit mathematical or statistical operations that produce the time series analysis result to be used as a latent candidate feature. In synthesizing the comprehensive framework for building a predictive model based on time series data elements, we identified at least four classes of data that can be used in the model design. The first two classes are shared with traditional multivariate models: multivariate data and clinical latent features. Multivariate data is represented by the standard one value per variable paradigm and is widely employed in a host of clinical models and tools. These are often represented by a number present in a given cell of a table. Clinical latent features derived, rather than directly measured, data elements that more accurately represent a particular clinical phenomenon than any of the directly measured data elements in isolation. The second two classes are unique to the time series data elements. The first of these is the raw data elements. These are represented by multiple values per variable, and constitute the measured observations that are typically available to end users when they review time series data. These are often represented as dots on a graph. The final class of data results from performing time series analysis. This class of data represents the fundamental concept on which our hypothesis is based. The specific statistical or mathematical operations are up to the modeler to determine, but we generally recommend that a variety of analyses be performed in order to maximize the likelihood that a representation of the time series data elements is produced that is able to distinguish between two or more classes of outcomes. The second manuscript, entitled "Building Clinical Prediction Models Using Time Series Data: Modeling Cardiac Arrest in a Pediatric ICU" provides a detailed description, start to finish, of the methods required to prepare the data, build, and validate a predictive model that uses the time series data elements determined in the first paper. One of the fundamental tenets of the second paper is that manual implementations of time series based models are unfeasible due to the relatively large number of data elements and the complexity of preprocessing that must occur before data can be presented to the model. Each of the seventeen steps is analyzed from the perspective of how it may be automated, when necessary. We identify the general objectives and available strategies of each of the steps, and we present our rationale for choosing a specific strategy for each step in the case of predicting cardiac arrest in a pediatric intensive care unit. Another issue brought to light by the second paper is that the individual steps required to use time series data for predictive modeling are more numerous and more complex than those used for modeling with traditional multivariate data. Even after complexities attributable to the design phase (addressed in our first paper) have been accounted for, the management and manipulation of the time series elements (the preprocessing steps in particular) are issues that are not present in a traditional multivariate modeling paradigm. In our methods, we present the issues that arise from the time series data elements: defining a reference time; imputing and reducing time series data in order to conform to a predefined structure that was specified during the design phase; and normalizing variable families rather than individual variable instances. The final manuscript, entitled: "Using Time-Series Analysis to Predict Cardiac Arrest in a Pediatric Intensive Care Unit" presents the results that were obtained by applying the theoretical construct and its associated methods (detailed in the first two papers) to the case of cardiac arrest prediction in a pediatric intensive care unit. Our results showed that utilizing the trend analysis from the time series data elements reduced the number of classification errors by 73%. The area under the Receiver Operating Characteristic curve increased from a baseline of 87% to 98% by including the trend analysis. In addition to the performance measures, we were also able to demonstrate that adding raw time series data elements without their associated trend analyses improved classification accuracy as compared to the baseline multivariate model, but diminished classification accuracy as compared to when just the trend analysis features were added (ie, without adding the raw time series data elements). We believe this phenomenon was largely attributable to overfitting, which is known to increase as the ratio of candidate features to class examples rises. Furthermore, although we employed several feature reduction strategies to counteract the overfitting problem, they failed to improve the performance beyond that which was achieved by exclusion of the raw time series elements. Finally, our data demonstrated that pulse oximetry and systolic blood pressure readings tend to start diminishing about 10-20 minutes before an arrest, whereas heart rates tend to diminish rapidly less than 5 minutes before an arrest.

Intensive care unit utilization among patients with cancer at the end of life

Over the last 2 decades, survival rates in critically ill cancer patients have improved. Despite the increase in survival, the intensive care unit (ICU) continues to be a location where end-of-life care takes place. More than 20% of deaths in the United States occur after admission to an ICU, and as baby boomers reach the seventh and eighth decades of their lives, the volume of patients in the ICU is predicted to rise. The aim of this study was to evaluate intensive care unit utilization among patients with cancer who were at the end of life. End of life was defined using decedent and high-risk cohort study designs. The decedent study evaluated characteristics and ICU utilization during the terminal hospital stay among patients who died at The University of Texas MD Anderson Cancer Center during 2003-2007. The high-risk cohort study evaluated characteristics and ICU utilization during the index hospital stay among patients admitted to MD Anderson during 2003-2007 with a high risk of in-hospital mortality. Factors associated with higher ICU utilization in the decedent study included non-local residence, hematologic and non-metastatic solid tumor malignancies, malignancy diagnosed within 2 months, and elective admission to surgical or pediatric services. Having a palliative care consultation on admission was associated with dying in the hospital without ICU services. In the cohort of patients with high risk of in-hospital mortality, patients who went to the ICU were more likely to be younger, male, with newly diagnosed non-metastatic solid tumor or hematologic malignancy, and admitted from the emergency center to one of the surgical services. A palliative care consultation on admission was associated with a decreased likelihood of having an ICU stay. There were no differences in ethnicity, marital status, comorbidities, or insurance status between patients who did and did not utilize ICU services. Inpatient mortality probability models developed for the general population are inadequate in predicting in-hospital mortality for patients with cancer. The following characteristics that differed between the decedent study and high-risk cohort study can be considered in future research to predict risk of in-hospital mortality for patients with cancer: ethnicity, type and stage of malignancy, time since diagnosis, and having advance directives. Identifying those at risk can precipitate discussions in advance to ensure care remains appropriate and in accordance with the wishes of the patient and family.^

A Time-Motion Study of Registered Nurses’ Workflow in Intensive Care Unit Remote Monitoring

Utilizing advanced information technology, Intensive Care Unit (ICU) remote monitoring allows highly trained specialists to oversee a large number of patients at multiple sites on a continuous basis. In the current research, we conducted a time-motion study of registered nurses’ work in an ICU remote monitoring facility. Data were collected on seven nurses through 40 hours of observation. The results showed that nurses’ essential tasks were centered on three themes: monitoring patients, maintaining patients’ health records, and managing technology use. In monitoring patients, nurses spent 52% of the time assimilating information embedded in a clinical information system and 15% on monitoring live vitals. System-generated alerts frequently interrupted nurses in their task performance and redirected them to manage suddenly appearing events. These findings provide insight into nurses’ workflow in a new, technology-driven critical care setting and have important implications for system design, work engineering, and personnel selection and training.

Study of length of stay in the cardiovascular intensive care unit

Coronary artery bypass graft (CABG) surgery is among the most common operations performed in the United States and accounts for more resources expended in cardiovascular medicine than any other single procedure. CABG surgery patients initially recover in the Cardiovascular Intensive Care Unit (CVICU). The post-procedure CVICU length of stay (LOS) goal is two days or less. A longer ICU LOS is associated with a prolonged hospital LOS, poor health outcomes, greater use of limited resources, and increased medical costs. ^ Research has shown that experienced clinicians can predict LOS no better than chance. Current CABG surgery LOS risk models differ greatly in generalizability and ease of use in the clinical setting. A predictive model that identified modifiable pre- and intra-operative risk factors for CVICU LOS greater than two days could have major public health implications as modification of these identified factors could decrease CVICU LOS and potentially minimize morbidity and mortality, optimize use of limited health care resources, and decrease medical costs. ^ The primary aim of this study was to identify modifiable pre-and intra-operative predictors of CVICU LOS greater than two days for CABG surgery patients with cardiopulmonary bypass (CPB). A secondary aim was to build a probability equation for CVICU LOS greater than two days. Data were extracted from 416 medical records of CABG surgery patients with CPB, 50 to 80 years of age, recovered in the CVICU of a large teaching, referral hospital in southeastern Texas, during the calendar year 2004 and the first quarter of 2005. Exclusion criteria included Diagnosis Related Group (DRG) 106, CABG surgery without CPB, CABG surgery with other procedures, and operative deaths. The data were analyzed using multivariate logistic regression for an alpha=0.05, power=0.80, and correlation=0.26. ^ This study found age, history of peripheral arterial disease, and total operative time equal to and greater than four hours to be independent predictors of CVICU LOS greater than two days. The probability of CVICU LOS greater than two days can be calculated by the following equation: -2.872941 +.0323081 (age in years) + .8177223 (history of peripheral arterial disease) + .70379 (operative time). ^

Nosocomial infections and their relationship to non-traditional risk factors in a medical intensive care unit

Background. Nosocomial infections are a source of concern for many hospitals in the United States and worldwide. These infections are associated with increased morbidity, mortality and hospital costs. Nosocomial infections occur in ICUs at a rate which is five times greater than those in general wards. Understanding the reasons for the higher rates can ultimately help reduce these infections. The literature has been weak in documenting a direct relationship between nosocomial infections and non-traditional risk factors, such as unit staffing or patient acuity.^ Objective. To examine the relationship, if any, between nosocomial infections and non-traditional risk factors. The potential non-traditional risk factors we studied were the patient acuity (which comprised of the mortality and illness rating of the patient), patient days for patients hospitalized in the ICU, and the patient to nurse ratio.^ Method. We conducted a secondary data analysis on patients hospitalized in the Medical Intensive Care Unit (MICU) of the Memorial Hermann- Texas Medical Center in Houston during the months of March 2008- May 2009. The average monthly values for the patient acuity (mortality and illness Diagnostic Related Group (DRG) scores), patient days for patients hospitalized in the ICU and average patient to nurse ratio were calculated during this time period. Active surveillance of Bloodstream Infections (BSIs), Urinary Tract Infections (UTIs) and Ventilator Associated Pneumonias (VAPs) was performed by Infection Control practitioners, who visited the MICU and performed a personal infection record for each patient. Spearman's rank correlation was performed to determine the relationship between these nosocomial infections and the non-traditional risk factors.^ Results. We found weak negative correlations between BSIs and two measures (illness and mortality DRG). We also found a weak negative correlation between UTI and unit staffing (patient to nurse ratio). The strongest positive correlation was found between illness DRG and mortality DRG, validating our methodology.^ Conclusion. From this analysis, we were able to infer that non-traditional risk factors do not appear to play a significant role in transmission of infection in the units we evaluated.^

An outbreak of Multi-Drug Resistant Acinetobacter in the burn intensive care unit of a large tertiary care center

Risk factors for Multi-Drug Resistant Acinetobacter (MDRA) acquisition were studied in patients in a burn intensive care unit (ICU) where there was an outbreak of MDRA. Forty cases were matched with eighty controls based on length of stay in the Burn ICU and statistical analysis was performed on data for several different variables. Matched analysis showed that mechanical ventilation, transport ventilation, number of intubations, number of bronchoscopy procedures, total body surface area burn, and prior Methicillin Resistant Staphylococcus aureus colonization were all significant risk factors for MDRA acquisition. ^ MDRA remains a significant threat to the burn population. Treatment for burn patients with MDRA is challenging as resistance to antibiotics continues to increase. This study underlined the need to closely monitor the most critically ill ventilated patients during an outbreak of MDRA as they are the most at risk for MDRA acquisition.^

Prediction of sepsis in the burn intensive care unit patient

Sepsis is a significant cause for multiple organ failure and death in the burn patient, yet identification in this population is confounded by chronic hypermetabolism and impaired immune function. The purpose of this study was twofold: 1) determine the ability of the systemic inflammatory response syndrome (SIRS) and American Burn Association (ABA) criteria to predict sepsis in the burn patient; and 2) develop a model representing the best combination of clinical predictors associated with sepsis in the same population. A retrospective, case-controlled, within-patient comparison of burn patients admitted to a single intensive care unit (ICU) was conducted for the period January 2005 to September 2010. Blood culture results were paired with clinical condition: "positive-sick"; "negative-sick", and "screening-not sick". Data were collected for the 72 hours prior to each blood culture. The most significant predictors were evaluated using logistic regression, Generalized Estimating Equations (GEE) and ROC area under the curve (AUC) analyses to assess model predictive ability. Bootstrapping methods were employed to evaluate potential model over-fitting. Fifty-nine subjects were included, representing 177 culture periods. SIRS criteria were not found to be associated with culture type, with an average of 98% of subjects meeting criteria in the 3 days prior. ABA sepsis criteria were significantly different among culture type only on the day prior (p = 0.004). The variables identified for the model included: heart rate>130 beats/min, mean blood pressure<60 mmHg, base deficit<-6 mEq/L, temperature>36°C, use of vasoactive medications, and glucose>150 mg/d1. The model was significant in predicting "positive culture-sick" and sepsis state, with AUC of 0.775 (p < 0.001) and 0.714 (p < .001), respectively; comparatively, the ABA criteria AUC was 0.619 (p = 0.028) and 0.597 (p = .035), respectively. SIRS criteria are not appropriate for identifying sepsis in the burn population. The ABA criteria perform better, but only for the day prior to positive blood culture results. The time period useful to diagnose sepsis using clinical criteria may be limited to 24 hours. A combination of predictors is superior to individual variable trends, yet algorithms or computer support will be necessary for the clinician to find such models useful. ^

Hemodynamic changes associated with manual and automated lateral rotation in mechanically ventilated intensive care patients

Objective: To investigate hemodynamic responses to lateral rotation. ^ Design: Time-series within a randomized controlled trial pilot study. ^ Setting: A medical intensive care unit (ICU) and a medical-surgical ICU in two tertiary care hospitals. ^ Patients: Adult patients receiving mechanical ventilation. ^ Interventions: Two-hourly manual or continuous automated lateral rotation. ^ Measurements and Main Results: Heart rate (HR) and arterial pressure were sampled every 6 seconds for > 24 hours, and pulse pressure (PP) was computed. Turn data were obtained from a turning flow sheet (manual turn) or with an angle sensor (automated turn). Within-subject ensemble averages were computed for HR, mean arterial pressure (MAP), and PP across turns. Sixteen patients were randomized to either the manual (n = 8) or automated (n = 8) turn. Three patients did not complete the study due to hemodynamic instability, bed malfunction or extubation, leaving 13 patients (n = 6 manual turn and n = 7 automated turn) for analysis. Seven patients (54%) had an arterial line. Changes in hemodynamic variables were statistically significant increases ( p < .05), but few changes were clinically important, defined as ≥ 10 bpm (HR) or ≥ 10 mmHg (MAP and PP), and were observed only in the manual-turn group. All manual-turn patients had prolonged recovery to baseline in HR, MAP and PP of up to 45 minutes (p ≤ .05). No significant turning-related periodicities were found for HR, MAP, or PP. Cross-correlations between variables showed variable lead-lag relations in both groups. A statistically, but not clinically, significant increase in HR of 3 bpm was found for the manual-turn group in the back compared with the right lateral position ( F = 14.37, df = 1, 11, p = .003). ^ Conclusions: Mechanically ventilated critically ill patients experience modest hemodynamic changes with manual lateral rotation. A clinically inconsequential increase in HR, MAP, and PP may persist for up to 45 minutes. Automated lateral rotation has negligible hemodynamic effects. ^

Epidemiology of Acute Lung Injury and Acute Respiratory Distress Syndrome in children in Vietnam

Acute Lung Injury (ALI) and Acute Respiratory Distress Syndrome (ARDS) are life- threatening disorders that can result from many severe conditions and diseases. Since the American European Consensus Conference established the internationally accepted definition of ALI and ARDS, the epidemiology of pediatric ALI/ARDS has been described in some developed countries. In the developing world, however, there are very few data available regarding the burden, etiologies, management, outcome, and factors associated with outcomes of ALI/ARDS in children. ^ Therefore, we conducted this observational, clinical study to estimate the prevalence and case mortality rate of ALI/ARDS among a cohort of patients admitted to the pediatric intensive care unit (PICU) of the National Hospital of Pediatrics in Hanoi, the largest children's hospital in Vietnam. Etiologies and predisposing factors, and management strategies for pediatric ALI/ARDS were described. In addition, we determined the prevalence of HIV infection among children with ALI/ARDS in Vietnam. We also identified the causes of mortality and predictors of mortality and prolonged mechanical ventilation of children with ALI/ARDS. ^ A total of 1,051 patients consecutively admitted to the pediatric intensive care unit from January 2011 to January 2012 were screened daily for development of ALI/ARDS using the American-European Consensus Conference Guidelines. All identified patients with ALI/ARDS were followed until hospital discharge or death in the hospital. Patients' demographic and clinical data were collected. Multivariable logistic regression models were developed to identify independent predictors of mortality and other adverse outcome of ALI/ARDS. ^ Prevalence of ALI and ARDS was 9.6% (95% confidence interval, 7.8% to 11.4%) and 8.8% (95% confidence interval, 7.0% to 10.5%) of total PICU admissions, respectively. Infectious pneumonia and sepsis were the most common causes of ALI/ARDS accounting for 60.4% and 26.7% of cases, respectively. Prevalence of HIV infection among children with ALI/ARDS was 3.0%. The case fatality rate of ALI/ARDS was 63.4% (95% confidence interval, 53.8% to 72.9%). Multiple organ failure and refractory hypoxemia were the main causes of death. Independent predictors of mortality and prolonged mechanical ventilation were male gender, duration of intensive care stay prior to ALI/ARDS diagnosis, level of oxygenation defect measured by PaO2/FiO2 ratio at ALI/ARDS diagnosis, presence of non-pulmonary organ dysfunction at day one and day three after ALI/ARDS diagnosis, and presence of hospital acquired infection. ^ The results of this study demonstrated that ALI/ARDS was a common and severe condition in children in Vietnam. The level of both pulmonary and non-pulmonary organ damage influenced survival of patients with ALI/ARDS. Strategies for preventing ALI/ARDS and for clinical management of the disease are necessary to reduce the associated risks.^

A case-control study of medication-associated acute kidney injuries in hospitalized pediatric patients

Acute kidney Injury (AKI) in hospitalized pediatric patients can be a significant event that can result in increased patient morbidity and mortality. The incidence of medication associated AKI is increasing in the pediatric population. Currently, there are no data to quantify the risks of developing AKI for various potentially nephrotoxic medications. The primary objective of this study was to determine the odds of nephrotoxic medication exposure in hospitalized pediatric patients with AKI as defined by the pediatric modified pRIFLE criteria. A retrospective case-control study was performed with patients that developed AKI, as defined by the pediatric pRIFLE criteria, as cases, and patients without AKI as controls that were matched by age category, gender, and disease state. Patients between 1 day and 18 years of age, admitted to a non-intensive care unit at Texas Children's Hospital for at least 3 days, and had at least 2 serum creatinine values drawn were included. Patient data was analyzed with Student's t test, Mann-Whitney U test, Chi square analysis, ANOVA, and conditional logistic regression. ^ Out of 1,660 patients identified for inclusion, 561 (33.8%) patients had AKI, and 357 cases were matched with 357 controls to become pairs. Of the cases, 441 were category 'R', 117 category 'I', 3 patients were category 'F', and no patient died. Cases with AKI were significantly younger than controls (p < 0.05). Significantly longer hospital length of stays, increased hospital costs, and exposure to more nephrotoxic medications for a longer period of time were characteristics of patients with AKI compared to patient without AKI. Patients with AKI had greater odds of exposure to one or more nephrotoxic medication than patients without AKI (OR 1.3, 95% CI 1.1–1.4, p < 0.05). Percent changes in estimated creatinine clearance (eCCl) from baseline were greatest with increased number of nephrotoxic medication exposures. ^ Exposure to potentially nephrotoxic medications may place pediatric patients at greater risk of acute kidney injury. Multiple nephrotoxic medication exposure may confer a greater risk of development of acute kidney injury, and result in increased hospital costs and patient morbidity. Due to the high percentage of patients that were exposed to potentially nephrotoxic medications, monitoring and medication selection strategies may need to be altered to prevent or minimize risk.^

Intensive care for extreme prematurity--moving beyond gestational age.

BACKGROUND: Decisions regarding whether to administer intensive care to extremely premature infants are often based on gestational age alone. However, other factors also affect the prognosis for these patients. METHODS: We prospectively studied a cohort of 4446 infants born at 22 to 25 weeks' gestation (determined on the basis of the best obstetrical estimate) in the Neonatal Research Network of the National Institute of Child Health and Human Development to relate risk factors assessable at or before birth to the likelihood of survival, survival without profound neurodevelopmental impairment, and survival without neurodevelopmental impairment at a corrected age of 18 to 22 months. RESULTS: Among study infants, 3702 (83%) received intensive care in the form of mechanical ventilation. Among the 4192 study infants (94%) for whom outcomes were determined at 18 to 22 months, 49% died, 61% died or had profound impairment, and 73% died or had impairment. In multivariable analyses of infants who received intensive care, exposure to antenatal corticosteroids, female sex, singleton birth, and higher birth weight (per each 100-g increment) were each associated with reductions in the risk of death and the risk of death or profound or any neurodevelopmental impairment; these reductions were similar to those associated with a 1-week increase in gestational age. At the same estimated likelihood of a favorable outcome, girls were less likely than boys to receive intensive care. The outcomes for infants who underwent ventilation were better predicted with the use of the above factors than with use of gestational age alone. CONCLUSIONS: The likelihood of a favorable outcome with intensive care can be better estimated by consideration of four factors in addition to gestational age: sex, exposure or nonexposure to antenatal corticosteroids, whether single or multiple birth, and birth weight. (ClinicalTrials.gov numbers, NCT00063063 [ClinicalTrials.gov] and NCT00009633 [ClinicalTrials.gov].).

Development and formative evaluation of an obesity prevention intervention for the pediatric primary care setting: Helping HAND (Healthy Activity and Nutrition Directions)

As the obesity epidemic continues to increase, the pediatric primary care office setting remains a relatively unexplored arena to offer obesity prevention interventions for children. The increased risk for adult obesity among 10 to 14 year-old children who are overweight, suggests obesity prevention programs should be introduced just before this age or early in this age period. Research is also accumulating on the importance of targeting parents along with children, since parents are in charge of the home environment for children. Therefore, the aim of this project was to develop an obesity prevention program called Helping HAND (Healthy Activity and Nutrition Directions) based on Social Cognitive Theory and authoritative parenting techniques for the pediatric primary care setting and conduct one-on-one interviews with parents as the initial formative evaluation of the intervention material for the obesity prevention intervention. A secondary aim of the project was to determine the feasibility of identifying appropriate subjects for the intervention, and conducting qualitative evaluations of the materials through recruitment through pediatric primary care settings. ^

Trauma care capacity and performance in Texas: Regional comparisons

Objective. The study reviewed one year of Texas hospital discharge data and Trauma Registry data for the 22 trauma services regions in Texas to identify regional variations in capacity, process of care and clinical outcomes for trauma patients, and analyze the statistical associations among capacity, process of care, and outcomes. ^ Methods. Cross sectional study design covering one year of state-wide Texas data. Indicators of trauma capacity, trauma care processes, and clinical outcomes were defined and data were collected on each indicator. Descriptive analyses were conducted of regional variations in trauma capacity, process of care, and clinical outcomes at all trauma centers, at Level I and II trauma centers and at Level III and IV trauma centers. Multilevel regression models were performed to test the relations among trauma capacity, process of care, and outcome measures at all trauma centers, at Level I and II trauma centers and at Level III and IV trauma centers while controlling for confounders such as age, gender, race/ethnicity, injury severity, level of trauma centers and urbanization. ^ Results. Significant regional variation was found among the 22 trauma services regions across Texas in trauma capacity, process of care, and clinical outcomes. The regional trauma bed rate, the average staffed bed per 100,000 varied significantly by trauma service region. Pre-hospital trauma care processes were significantly variable by region---EMS time, transfer time, and triage. Clinical outcomes including mortality, hospital and intensive care unit length of stay, and hospital charges also varied significantly by region. In multilevel regression analysis, the average trauma bed rate was significantly related to trauma care processes including ambulance delivery time, transfer time, and triage after controlling for age, gender, race/ethnicity, injury severity, level of trauma centers, and urbanization at all trauma centers. Transfer time only among processes of care was significant with the average trauma bed rate by region at Level III and IV. Also trauma mortality only among outcomes measures was significantly associated with the average trauma bed rate by region at all trauma centers. Hospital charges only among outcomes measures were statistically related to trauma bed rate at Level I and II trauma centers. The effect of confounders on processes and outcomes such as age, gender, race/ethnicity, injury severity, and urbanization was found significantly variable by level of trauma centers. ^ Conclusions. Regional variation in trauma capacity, process, and outcomes in Texas was extensive. Trauma capacity, age, gender, race/ethnicity, injury severity, level of trauma centers and urbanization were significantly associated with trauma process and clinical outcomes depending on level of trauma centers. ^ Key words: regionalized trauma systems, trauma capacity, pre-hospital trauma care, process, trauma outcomes, trauma performance, evaluation measures, regional variations ^

Racial disparities in patient survival after liver transplantation in the United States

Background. Racial disparities in healthcare span such areas as access, outcomes after procedures, and patient satisfaction. Previous work suggested that minorities experience less healthcare and worse survival rates. In adult orthotopic liver transplantation (OLT) mixed results have been reported, with some showing African-American recipients having poor survival compared to Caucasians, and others finding no such discrepancy. ^ Purpose. This study’s purpose was to analyze the most recent United Network for Organ Sharing (UNOS) data, both before and after the implementation of the Model for End-Stage Liver Disease (MELD)/Pediatric End-Stage Liver Disease (PELD) scoring system, to determine if minority racial groups still experience poor outcomes after OLT. ^ Methods. The UNOS dataset for 1992-2001 (Era I) and 2002-2007 (Era II) was used. Patient survival rates for each Era and for adult and pediatric recipients were analyzed with adjustment. A separate multivariate analysis was performed on African-American adult patients in Era II in order to identify unique predictors for poor patient survival. ^ Results. The overall study included 66,118 OLT recipients. The majority were Caucasian (78%), followed by Hispanics (13%) and African-Americans (9%). Hispanic and African-American adults were more likely to be female, have Hepatitis C, to be in the intensive care unit (ICU) or ventilated at time of OLT, to have a MELD score ≥23, to have a lower education level, and to have public insurance when compared to Caucasian adults (all p-values < 0.05). Hispanic and African-American pediatric recipients were more likely have public insurance and less likely to receive a living donor OLT than were Caucasian pediatric OLT recipients (p <0.05). There was no difference in the likelihood of having a PELD score ≥21 among racial groups (p >0.40). African-American adults in Era I and Era II had worse patient survival rates than both Caucasians and Hispanic (pair-wise p-values <0.05). This same disparity was seen for pediatric recipients in Era I, but not in Era II. Multivariate analysis of African-American recipients revealed no unique predictors of patient death. ^ Conclusions. African-American race is still a predictor of poor outcome after adult OLT, even after adjustment for multiple clinical, demographic, and liver disease severity variables. Although African-American and Hispanic subgroups share many characteristics previously thought to increase risk of post-OLT death, only African-American patients have poor survival rates when compared to Caucasians. ^